Abstract
In five years, MPAI – Moving Picture, Audio, and Data Coding by Artificial Intelligence, the international, unaffiliated, not-for-profit association developing standards for AI-based data coding – has been carrying out its mission, making its results widely known and its status recognised. However, not all are clear why MPAI was established, which are its distinctive features, and why it stands out among the organisations developing standards.
This is the first of a series of articles that will revisit the driving force that allowed MPAI to develop 15 standards in a variety of fields where AI can make the difference and have half a score under development. The articles will pave the way for the next five years of MPAI.
1 Standards have a divine nature
MPAI was established as a Swiss not-for-profit organisation on 30 September 2020 with the mission of developing data coding standards based on Artificial Intelligence. The first element that has driven MPAI into existence is the very word STANDARD. If you ask people “what is a standard?” you are likely to obtain a wide range of responses. The simplest, most effective, and although rather obscure answer is instead “a tool that connects minds”. A standard establishes a paradigm that allows a mind to interpret what another mind expresses in words or by other means of communication.
The easiest example of standard is language itself. A language assigns labels – words – to physical and intellectual objects. Apparently, the language-defined labels are what make humans different from animals, even though there are innumerable forms of language used by animals that are less rich than the human one.
Words have a divine nature. So, it is no surprise that St. John’s Gospel starts with the sentence “In the beginning was the Word, and the Word was with God, and God was the Word”.
Is this divine nature only applicable to language? Well, no. If we say that 20 mm of rain fell in 4 hours, we are using the language to convey information about rain that would be void of a quantitative value if there was not a standard for length called meter and a standard for time called hour.
Next to these lofty goals, standards have other practical purposes, A technical standard enacted by a country may be used as a tool to limit and sometimes even outlaw products not conforming to that standard, in that country. The existence of standards used for this purpose was the main driver toward the establishment of the Moving Picture Experts Group (MPEG): a single digital video standard that eventually uprooted scores of analogue television standards, with myriads of sub-standards. The intention was to nullify this malignant use of standards.
The goal of MPEG was to serve humans by enabling them to hear and see, thanks to machines that were able to “understand” the bits generated by other machines. In other words, it was necessary that machines be made able to understand the “words” of other machines.
Come 2020, Artificial Intelligence was not yet in the headlines, but the direction was clear. AI systems would be endowed with more and more “intelligence”, communicate between each other, and let humans communicate with them. What forms the “word” would take were not clear, but that the forms would be manifold was.
While MPEG had ushered in a new spirit in standardisation, it had also fostered a transformation in the way the need for standards would take shape and how standards would be exploited. In the early MPEG days, most industries still had research laboratories where the advancement of technology was monitored and fostered with a view of exploiting technology for new products and services. New findings would be patented and new patent-based products launched. The market would bless the winner among different products doing more or less the same thing with different technologies.
MPEG rendered useless the costly step of battling on patents in the market bringing to the standards committee a battle on standards. As a patent in a successful standard was highly remunerative, it did not take much time for the industry to invest in any patentable research. By industry, we intend “any” industry, actually not even industries that had a business in products and services. The idea was that a day would come that a patent would be needed in “a” standard. That single patent would repay the tens-hundreds-thousands of unused patents.
This was significant progress in terms of optimising efforts to generate innovation, and letting more actors join the fray. That progress, however, came at a cost, the disconnect of exploitation from generating innovation. An industry that had made an innovation to achieve an investment had every interest to see that innovation deployed. A company that has a portfolio of 10,000 patents may decide not to license a patent (in practice, by dragging its feet in releasing a patent) if that helps it license a more remunerative patent instead.
Certainly, this epochal evolution has resulted in a more efficient generation of innovation but is actually hindering exploitation of valuable innovations.
